In conventional data processing using the eigenspace method, for example, several images that are subjected to pattern recognition are compared with a database, and a common threshold for similarity is used.
For example, there is known a method which, when comparing a face photograph with an input face image, improves the method described above to extract features by separating a model space from a variation space (see patent document 1).
However, the data processing is not performed in terms of whether there is a portion similar to an image on one sheet or a series of sounds (such as an image or a word) or whether there is a portion different from an image on a sheet or a series of sounds (such as an image or a word).
In this type of data processing, a characteristic value and a characteristic vector related to the result of analysis of a main ingredient of each piece of data are often calculated in advance and stored in a database. Moreover, also in comparison data, its main ingredient is calculated from the characteristic value and the characteristic vector stored in the database.
For example, there is known a behavior analysis device which stores, in a database, the average value of a feature vector, a covariance matrix and a characteristic value matrix and a characteristic vector of the covariance matrix and uses them. (see patent document 2 (in particular, see claim 6)).
Patent document 1: Japanese Patent Application the KOKAI Publication No. H10-171988
Patent document 2: Japanese Patent Application the KOKAI Publication No. 2004-157614
Disadvantageously, however, it is impossible to simultaneously perform, on division data (data obtained by dividing an image) and the like, processing for calculating the characteristic value and the characteristic vector and the analysis of a main ingredient in a real-time manner.